John Holodnak
Dr. John Holodnak is a technical staff member in the Artificial Intelligence Technology and Systems Group. He joined MIT Lincoln Laboratory in June 2015. His primary research interests are uncertainty quantification, the loss landscapes of neural networks, evaluation of machine learning systems using uncertain ground truth, and numerical linear algebra.
Holodnak received a BS degree in mathematics in 2010 from Ohio Northern University and a PhD degree in applied mathematics in 2015 from North Carolina State University. His dissertation was titled “Topics in Randomized Algorithms for Numerical Linear Algebra” and presented new analysis of sampling techniques relevant to matrix computations. His graduate education was supported by a fellowship from the U.S. Department of Education.